Heather Britt

Neighborhood Level Spatial Analysis of the Relationship Between Alcohol Outlet Density and Criminal Violence

Misuse of alcohol is a significant public health problem, potentially resulting in unintentional injuries, motor vehicle crashes, drownings, and, perhaps of greatest concern, serious acts of violence, including assaults, rapes, suicides, and homicides. Although previous research establishes a link between alcohol consumption increased levels of violence, studies relating the density of alcohol outlets (e.g., restaurants, bars, liquor stores) and the likelihood of violent crime have been less common. In this paper we test for such a relationship at the small area level, using data from 79 neighborhoods in the city of Minneapolis, Minnesota. We adopt a fully Bayesian point of view using Markov chain Monte Carlo (MCMC) computational methods as available in the popular and freely available WinBUGS language. Our models control for important covariates (e.g., neighborhood racial heterogeneity, age heterogeneity) and also account for spatial association in unexplained variability using conditionally autoregressive (CAR) random effects. Our results indicate a significant positive relationship between alcohol outlet density and violent crime, while also permitting easy mapping of neighborhood-level predicted and residual values, the former useful for intervention in the most at-risk neighborhoods and the latter potentially useful in identifying covariates still missing from the fixed effects portion of the model.

Care guides: employing nonclinical laypersons to help primary care teams manage chronic disease.

Lay persons (“care guides”) without previous clinical experience were hired by a primary care clinic, trained for 2 weeks, and assigned to help 332 patients and their providers manage their diabetes, hypertension, and congestive heart failure. One year later, failure by these patients to meet nationally recommended guidelines was reduced by 28%, P < .001. Improvement was seen in tobacco usage, blood pressure control, pneumonia vaccination, low-density lipoprotein cholesterol levels, annual eye examinations, aspirin use, and microalbuminuria testing. Care guides served an average of 111 patients at an annual per patient cost of

The Heart of New Ulm Project: Using Community-Based Cardiometabolic Risk Factor Screenings in a Rural Population Health Improvement Initiative

392. Further testing of this model is warranted.

Reactions of nurses to the use of electronic health record alert features in an inpatient setting.

Awareness of cardiovascular disease and diabetes risk factors can improve the health of individuals and populations. Community-based risk factor screening programs may be particularly useful for quantifying the burden of cardiometabolic risk in a given population, particularly in underserved areas. This study provided a description of a screening platform and how it has been used to monitor the cardiometabolic risk profile within the broader Heart of New Ulm Project, which is based in a rural Minnesota community. A cross-sectional, descriptive examination of baseline screening data indicated that 45% of the target population participated in the program over 8 months. Overall, 13% of the sample reported a personal history of diabetes or cardiovascular disease. Among the subset without active cardiometabolic disease, 35% were found to be at high risk for developing cardiovascular disease or type 2 diabetes over the next 8-10 years. A high prevalence of metabolic syndrome, high low-density lipoprotein cholesterol, obesity, and low fruit/vegetable consumption were of particular concern in this community. This article describes the use of screening results to inform the design of intervention programs that target these risk factors at both the community and individual levels. In addition, design considerations for future community-based cardiometabolic risk factor screening programs are discussed, with a focus on balancing program objectives related to health surveillance, research, and the delivery of preventive health care services.

Stress and workplace productivity loss in the heart of new ulm project

While studies have been conducted to assess nurse perception of electronic health records, once electronic health record systems are up and running, there is little to guide the use of features within the electronic health record for nursing practice. Alerts are a promising tool for implementing best practice for patient care in inpatient settings. Yet the use of alerts for inpatient nursing is understudied. This study examined nurse attitudes and reactions to alerts in the inpatient setting. Focus groups were conducted at three hospitals with 50 nurses. Nurses were asked about five different alert features. For each alert, participants were asked about their feelings and reactions to the alert, how alerts help or hinder work, and suggestions for improvements. Findings include clear preferences for alert types and content. Nurses preferred a dashboard style alert with functions included to accomplish tasks directly in the alert. While nurses reported positive reactions to certain alert pages, they also reported low use of those features and occasional distrust of the data included in alerts. Findings provide guidance for future use of alerts and design of new alerts. Findings also identify the important challenge of designing and implementing alerts for integration with nursing workflow.

Extending Our Understanding of Burnout and Its Associated Factors: Providers and Staff in Primary Care Clinics.

Objective: The impact of stress in conjunction with lifestyle factors on workplace productivity is understudied, thus the relationship between these variables was examined. Methods: Negative binomial regression was used to test the cross-sectional association between stress and productivity loss in a sample of 2823 adults. Results: After body mass index adjustment, there was an interaction between stress and physical activity (&bgr; ± SE = 0.002 ± 0.001, P = 0.033). Active participants with low stress had 2% estimated productivity loss, whereas active participants with high stress had more than 11% productivity loss. Other lifestyle factors were not significant. Conclusions: Higher stress generally predicted greater productivity loss, but this association varied. At low stress, more activity was associated with less productivity loss. At high stress, more activity was associated with more productivity loss, perhaps indicating that individuals cope by exercising more and working less.

Effect of a Whole-Person Model of Care on Patient Experience in Patients With Complex Chronic Illness in Late Life

Burnout has been identified as an occupational hazard in the helping professions for many years and is often overlooked, as health-care systems strive to improve cost and quality. The Maslach Burnout Inventory (MBI) and the Areas of Worklife Survey (AWS) are tools for assessing burnout prevalence and its associated factors. We describe how we used them in outpatient clinics to assess burnout for multiple job types. Traditional statistical techniques and seemingly unrelated regression were used to describe the sample and evaluate the association between work life domains and burnout. Of 838 eligible participants, 467 (55.7%) were included for analysis. Burnout prevalence varied across three job categories: providers (37.5%), clinical assistants (24.6%), and other staff (28.0%). It was not related to age, gender, or years of tenure but was lower in part-time workers (24.6%) than in full-time workers (33.9%). Analysis of the AWS subscales identified organizational correlates of burnout. Accurately identifying and defining the operative system factors associated with burnout will make it possible to create successful interventions. Using the MBI and the AWS together can highlight the relationship between system work experiences and burnout.

Quality of Life for Late Life Patients: Mixed-Methods Evaluation of a Whole-Person Approach for Patients With Chronic Illnesses:

Background: Patients with serious chronic illness are at a greater risk of depersonalized, overmedicalized care as they move into later life. Existing intervention research on person-focused care for persons in this transitional period is limited. Objective: To test the effects of LifeCourse, a team-based, whole-person intervention emphasizing listening to and knowing patients, on patient experience at 6 months. Design: This is a quasi-experimental study with patients allocated to LifeCourse and comparison groups based on 2 geographic locations. Robust change-score regression models adjusted for baseline differences and confounding. Setting/Participants: Patients (113 intervention, 99 comparison in analyses) were individuals with heart failure or other serious chronic illness, cancer, or dementia who had visits to hospitals at a large multipractice health system in the United States Midwest. Measurements: Primary outcome was 6-month change in patient experience measured via a novel, validated 21-item patient experience tool developed specifically for this intervention. Covariates included demographics, comorbidity score, and primary diagnosis. Results: At 6 months, LifeCourse was associated with a moderate improvement in overall patient experience versus usual care. Individual domain subscales for care team, communication, and patient goals were not individually significant but trended positively in the direction of effect. Conclusion: Person-focused, team-based interventions can improve patient experience with care at a stage fraught with overmedicalization and many care needs. Improvement in patient experience in LifeCourse represents the sum effect of small improvements across different domains/aspects of care such as relationships with and work by the care team.

Using Social Network Analysis to Identify Key Players within Clinical Teams for Improving Pain Management

Quality of life (QOL) for patients with serious illness in late life is important for patients and policy makers and has implications for improved care delivery. This mixed-methods evaluation examined the effectiveness of a new whole-person approach to late life care—the LifeCourse—which provides patients with ongoing, across-setting assistance from lay health care workers, supported by a clinical team. We investigated whether participation in LifeCourse improves QOL for intervention patients, compared with usual care controls. QOL was assessed using baseline and 6 months Functional Assessment of Chronic Illness Therapy–Palliative version tool (n = 181 patients and 126 controls). LifeCourse had a significant positive effect on overall QOL for patients when compared with controls. Interview data revealed that participants adjusted expectations when assessing QOL and actively sought out ways to maintain QOL with meaningful activities and needed services. LifeCourse offers a promising model for improving QOL for late life patients.

Propensity for and Correlates of Alcohol Sales to Underage Youth

The use of social network analysis to understand social relationships among individuals in healthcare is a relatively recent and innovative approach. This approach has been employed to study phenomena such as disease contagion, smoking cessation, and physical collaboration. This paper presents a social network analysis conducted among clinicians in three nursing units of a large metro hospital. The aim was to examine information flow with regard to pain management in addition to explore the evolving nature of the represented network over time. For the study, social network surveys were administered to investigate characteristics of three identified nursing units. Three network questions were used to explore relationships and information flow: (a) Who do you routinely work with on pain management? (b) Who do you get new ideas or inspiration from to help your pain management efforts? (c) Who would you like to work with in the future on pain management? Two surveys were conducted to collect data over time, and standard social network measures were computed to study the interaction network and its evolving nature. Data analysis provided insights into the nature of interactions within and across these groups and thereby successfully identified key players in information flow with regard to pain management.